Structural Control and Health Monitoring

Krause, Thomas; Ostermann, Jörn

doi: 10.1002/stc.2520pmid: N/A

When operating a wind turbine, damage of rotor blades is a serious problem. Undetected damages are likely to increase overtime, and therefore, the safety risks and economical burdens also increase. A monitoring system, which detects reliably defects in early stages, gives scope for action and is therefore a key element to avoid damage increase and to optimize the efficiency of wind turbines. One promising approach for damage detection is acoustic emission methods. Although most acoustic emission approaches use ultrasonic sound waves of the structure that require about 12 to 40 sensors to monitor one rotor blade, we propose to use the airborne sound in lower frequencies from about 500 Hz to 35 Hz with three optical microphones and present a signal model‐based damage detection algorithm. The real‐time algorithm uses six audio features from a spectrogram representation to detect damages and to estimate its significance. In a fatigue test of a 34‐m blade, the algorithm detected the damage event and damage increasing without false detection. It was also tested with recordings inside an operating blade of a 3.4‐MW wind turbine. In the recorded time period of about 1 year, the algorithm indicated no false detection.

Andreaus, Ugo; De Angelis, Maurizio

doi: 10.1002/stc.2517pmid: N/A

During strong earthquakes, structural pounding may occur between structures (buildings, bridges, strategic facilities, critical equipment, etc.) and the surrounding moat wall because of the limited separation distance and the deformations of the isolator. An arrangement that favors the solution of this problem is the interposition of shock absorbers. Thus, the influence of geometrical and mechanical characteristics of isolation and mitigation devices on nonlinear, nonsmooth response of vibro‐impact systems is experimentally investigated in this paper on the basis of a laboratory campaign of experimental tests. Shaking table tests were carried out under a harmonic excitation in order to investigate two different configurations: the absence and the presence of bumpers. Three different values of the table acceleration peak were applied, four different amplitude values of the total gap between mass and bumpers were considered, and also four different types of bumpers were employed; moreover, two problems were addressed, namely, control of excessive displacements and control of excessive accelerations, and hence, two types of normalization were adopted in order to better interpret experimental results. Suitable choices of pairs of bumpers and gaps were suggested as a trade‐off between conflicting objectives. Furthermore, a numerical model was proposed, and its governing parameters identified in order to simulate the experimental results.

Ding, Zhenghao; Li, Jun; Hao, Hong

doi: 10.1002/stc.2522pmid: N/A

The accuracy of structural damage identification is affected by the uncertainties in the vibration measurements and the finite element modeling. This paper proposes a novel approach based on sparse deep belief network (DBN) for structural damage identification with uncertain and limited data. Vibration characteristics, that is, natural frequencies and mode shapes, are extracted as the input to the network, while the output are the damage locations and severities of the structure. DBN is chosen to train the generated data sets and identify structural damages. Restricted Boltzmann Machines (RBMs) are used as building blocks to composite a DBN. To further enhance the capacity of the RBMs, an arctan‐based sparse constraint is utilized to enable the hidden units to become sparse. This is achieved by adding an arctan norm constraint on the whole of the hidden units' activation probabilities. Numerical and experimental studies are conducted to verify the accuracy and performance of the proposed method. Undetermined damage identification is conducted, in which the quantity of input modal data is less than that of the system parameters to be identified. The identification results show that the proposed sparse DBN based on arctan can identify the damage effectively, and its accuracy is better than those obtained by other methods, even when the modeling uncertainty and the measurement noise exist and only limited data is available.

doi: 10.1002/stc.2394pmid: N/A

No abstract is available for this article.

Rezaiee‐Pajand, Mohammad; Entezami, Alireza; Sarmadi, Hassan

doi: 10.1002/stc.2481pmid: N/A

An effective and reliable approach to updating finite element (FE) models of real structures is to utilize a sensitivity‐based strategy. A challenging issue concerning the sensitivity‐based finite element model updating (FEMU) is to create a well‐established framework for updating the inherent structural properties of FE models under incomplete noisy modal data. When noise contaminates the measured modal parameters, another challenging issue stems from the ill‐posedness of the FEMU inverse problem. This article proposes an innovative sensitivity‐based FEMU strategy based on the combination of modal kinetic energy and modal strain energy for simultaneously updating the element mass and stiffness matrices of FE models. The great novelty of this strategy is to get an idea from the unconstrained optimization problem for the establishment of a sensitivity‐based FEMU framework. The correction of the element mass and stiffness matrices in a simultaneous way is another novelty of the proposed FEMU strategy. Moreover, new iterative and hybrid regularization methods under the Krylov subspace theory and bidiagonalization process are presented to solve the ill‐posed inverse problem of FEMU. The accuracy and reliability of the proposed methods are numerically validated by a two‐story concrete frame and a two‐span continuous steel truss along with some comparative analyses. Results demonstrate that the suggested sensitivity‐based strategy and regularized solution methods are influential and successful in FEMU under incomplete noisy modal data.

Xia, Qi; Xia, Yong; Wan, Hua‐Ping; Zhang, Jian; Ren, Wei‐Xin

doi: 10.1002/stc.2521pmid: N/A

Expansion joints of bridges are vulnerable to damage due to the thermal expansion and contraction, vehicle traffic, and so forth. Currently, the temperature–displacement relationship model may be the only qualitative method for condition evaluation of bridge expansion joints using the field monitoring data. The quantitative assessment based on the finite element model updating techniques is heavy computational burden and time consuming. Therefore, a Gaussian process (GP) metamodel‐based model updating method is proposed in this study and performed for the quantitative identification on the boundary condition of the expansion joints of Jiangyin Suspension Bridge using the long‐term displacement and temperature monitoring data. At first, the relationship between the longitudinal boundary stiffness (LBS) and structural temperature is formulated on the basis of thermal effects of the bridge deck. The range of LBS is approximately estimated by the regression coefficients from 1‐year monitoring data and is used as initial bounds for the subsequent model updating procedure. The GP metamodel is formulated to map the relationship between the LBS and the longitudinal displacements under the thermal effects. The LBS identification of the Jiangyin Suspension Bridge is performed within the fast‐running GP metamodel. The results show that the longitudinal displacements using the updated LBS are in good agreement with the measurements, which verifies the effectiveness of GP metamodel‐based model updating method in identifying the LBS of the long‐span suspension bridge.

Gelman, Len; Petrunin, Ivan; Parrish, Colin; Walters, Mark

doi: 10.1002/stc.2479pmid: N/A

Diagnostics and elimination of airflow separation effects draw essential attention of researchers in the areas of energy generation, civil engineering, and aerospace due to unwanted and harmful interaction of separated airflow with different structures. In aviation, distortion of the intake airflows of an aircraft engine, known as intake separation, not only reduces the efficiency of the engine due to decrease in air intake but also interacts with engine structural components, for example, blades, significantly increasing their vibration. This leads to fatigue and subsequent accelerated failure of these components.

Salvatore, Russo; Eleonora, Spoldi

doi: 10.1002/stc.2493pmid: N/A

The aim of this paper is to identify, both through microtremor analysis and visual inspection, the collapse mechanisms of the Nepalese wood‐masonry monuments damaged by the 2015 seismic event that struck Kathmandu and its valley. The research analyses two case studies as the “Radha Krishna” temple located in Teku, a district in Kathmandu, and the “Pancha Deval complex” in Pashupati area. More specifically, after a careful anamnesis based on visual inspection and hypotheses on the temple's structural behaviour, global nondestructive testing (microtremor) was carried out for qualitative characterization of the structural system. The visual damage survey allowed to identify the recurring collapse mechanisms in the two case studies with the identification of typical Nepali expected damage. The case of Radha Krishna temple denotes a Nepali collapse mechanism typical in the corner of temples made of timber masonry, in which the mechanical contribution of the timber is manifested through columns and windows. The ambient vibration analysis carried out by tromograph device and microtremor evaluation allowed to dynamically characterize the two bases by identifying the peak frequencies both for Radha Krishna and for Pancha Deval complex. With the same device, the two historic constructions have been also studied in evaluating local modes and frequency. In the Pancha Deval complex, a relationship between damage, frequencies, and the amplification of the base was observed. In detail, the five buildings have similar damage and similar first frequencies (2.72–2.9 Hz). The most damaged sides are those with the frequencies close to the base (2.05–2.38 Hz).

Wu, Guang‐Ming; Yang, Dong‐Hui; Yi, Ting‐Hua; Li, Hong‐Nan; Liu, Hua

doi: 10.1002/stc.2515pmid: N/A

Sliding bearings of a bridge are important sliding elements that accommodate the bridge movement caused by temperature action and vehicle/wind load. The sliding life of sliding bearings is determined by the wear of the sliding materials in the bearing. However, the wear of sliding bearings primarily results from a large amount of cumulative sliding displacement experienced by the sliding bearing, even if the movement of the bridge under the vehicle/wind load is far less than the allowable design displacement of the sliding bearing. In general, bearing displacement is monitored using displacement gauges with a low sampling frequency, which cannot accurately capture the relatively high‐frequency displacement component caused by vehicle/wind loads. For predicting the sliding life of sliding bearings, this paper provides a mode rotation angle superposition approach to estimate cumulative sliding displacement. The estimation approach incorporates the combination of the rotation angles of bridge ends and the modal parameters of bridges. The feasibility and advantage of the estimation approach are illustrated by a numerical example; then, the influence factors of the error are analysed. Finally, sliding life prediction of sliding bearings is applied to an actual bridge using the estimation approach of cumulative sliding displacement.

Shakib, Arman; Ghorbani‐Tanha, Amir K.

doi: 10.1002/stc.2518pmid: N/A

An innovative semiactive device, named the spindle adaptive tuned vibration absorber (SATVA), is proposed herein, having the potential of attenuating unfavorable vibrations of the host systems. The proposed device includes a preferably spindle‐shaped body of mass, whose mass moment of inertia can be altered simply by moving a pair of rotating supports. Therefore, the natural frequency of the device can be altered with a fairly low power consumption. A comprehensive analytical approach is employed in order to derive the governing equations of motion of the device, considering physical and practical issues. Through a numerical case study, it is demonstrated that the device is capable of reducing unfavorable vibrations of a rotating machinery during start‐up, while requiring considerably less amount of physical mass, compared with conventional absorbers. In addition, the spindle adaptive tuned vibration absorber has a quite rapid adaptation mechanism in comparison with other adaptive‐mass tuned vibration absorbers. Provided that its absolute acceleration during operation can be kept within reasonable limits to prevent slipping, this device is capable of finding different applications in various engineering disciplines.